The present invention relates generally to medical imaging, and more particularly to PET/MR-based medical imaging.
PET/MR is a hybrid medical imaging modality in which a positron emission tomography (PET) scanner and a magnetic resonance (MR) scanner are integrated together into a single imaging system. In this combination, MR is typically used for anatomical imaging (which shows the physical structure of the anatomy being imaged) while PET is used for functional imaging (which shows the function or metabolism of the anatomy being imaged). The MR and PET images may be registered with each other with the functional PET images superimposed on the anatomical MR images, thereby showing the functional or metabolic activity in the imaged anatomy.
In PET imaging, the patient is typically injected with a radiopharmaceutical such as F18-fluorodeoxyglucose (FDG) which is essentially a radioactive form of glucose that emits positrons (i.e., positively charged particles of anti-matter). As the FDG is circulated throughout the patient's body, the glucose is metabolized by the tissues and organs. Meanwhile, the positrons being emitted from the FDG collide with nearby electrons in the surrounding tissue causing annihilation events, each of which causes a pair of 511 keV gamma photons to be emitted approximately 180 degrees from each other. The PET detectors (which are typically arrayed in a ring about the patient) gather these emitted photons, but first the photons must pass from the various points of annihilation through the patient's body. When two detectors detect a pair of photons within a given time window, and the line between the two detectors passes through the patient, it is assumed that the pair of photons originated at a point (an annihilation event location) somewhere near the midpoint of the line. (With the faster temporal resolution of time-of-flight (TOF) PET scanners, the difference in photon arrival times detected by the two detectors can be used to more precisely estimate the annihilation event location, than can non-TOF scanners.)
PET images are created by accumulating the line integrals of coincidence events between pairs of detectors, and reconstructing these line integrals among all the various detector pairs into images. However, the 511 keV gamma photons summed into these line integrals do not all pass through the same type or quantity of patient tissue. For example, if an annihilation event occurs near the skin surface on the right side of a patient's torso, one of the two resulting gamma photons may travel through a very small amount of skin tissue on the patient's right side before hitting and being detected by a detector on the PET detector ring, while the other gamma photon may travel through most of the patient's body (including through bone) before exiting the patient's left side and being detected by a detector on the opposite side of the detector ring. Thus, to optimally use these two detected gamma photons in the image reconstruction process, it is useful to know the particular anatomy through which each photon traveled on its path to the detectors since there is a probability that one or both photons will interact in the body and be lost, so that appropriate corrections can be made for this event loss probability. The process of determining the anatomy and using it to make these corrections is known as attenuation correction (AC). This correction is necessary (among other corrections) to accurately determine the radiotracer activity concentration that bio-distributes within the patient's body. A commonly used method for accomplishing AC in PET imaging is to utilize an X-ray-based computed tomography (CT) scan from a CT scanner. A CT scan can be used to create a “map” of the patient's anatomy (consisting of transverse multiple imaging slices taken through the patient), with various identifiable structures and/or tissue densities being assigned appropriate Hounsfield unit (HU) numbers representing the degree to which various tissues attenuate X-ray radiation (which is comprised of photons having energies of approximately 90-140 keV). This CT-based “attenuation map” can then be converted into a corresponding PET-based attenuation map which represents the degree to which various tissues attenuate 511 keV gamma photons. This attenuation map is then used to make appropriate corrections to the detected gamma photon data so that an attenuation-corrected PET image can be formed.
MR imaging is relatively accurate in the center of the MR field-of-view (FOV), but the images become distorted close to the FOV edges, both in the transverse and axial directions. This is illustrated in FIGS. 1-4, which compares phantom scans in CT and MR. FIG. 1 shows a spatial distortion phantom 10, which is constructed of multiple stacked planks 12 having holes milled into them at regular intervals. The holes are filled with fish oil capsules 14, which make good water-like signals for CT as well as provide good T1 signals for MR. The phantom 10 is imaged in a CT scanner, with a resulting transverse (x-y) image shown in FIG. 2. Note the minimal distortion across the CT FOV, as evidenced by the accurate representation of the oil capsule regular spacing throughout the FOV. The same phantom is then imaged in an MR scanner, with the resulting transverse (x-y plane) and coronal (x-z plane) scans shown in FIGS. 3 and 4, respectively. Both of the MR scans show accurate representations of the fish oil capsules 14 nearer to the centers of the FOVs, but the images of oil capsule placement become quite distorted toward the outer edges. Because of this distortion, MR has a limited effective FOV (at least as compared to CT, and for that matter as compared to PET as well), and the resulting images are typically “truncated”, either intentionally, so as to retain only the more accurate medial data and cut off or exclude the more distorted distal data, or incidentally/naturally as part of the MR image formation process.
This truncation creates a challenge for PET/MR systems which may utilize MR for AC rather than the more commonly used CT-based AC. Typical MR-based AC (MRAC) may utilize the following process. First, an MR scan is conducted to create MR images/data, such as by using the well-known T1-weighted, 2-point Dixon (LAVA-FLEX) pulse sequence. Second, the MR images are segmented into regions representative of different patient tissue types, such as fat, water, internal air (inside the patient, e.g., lungs) and background (air outside the patient). Third, appropriate (CT) HU values are assigned to each region, which creates a “pseudo-CT” mask 16, as illustrated in FIG. 5, which shows a transverse slice of a patient 40 through the torso 42 and arms 44. Note in FIG. 5 how at least one of the arms 44 has been truncated due to the limited MR DFOV (diameter of the in-plane x-y FOV), making the image of the truncated arm incomplete. Fourth, a non-attenuation corrected (NAC) PET image is reconstructed using time-of-flight (TOF) at the PET diameter FOV (DFOV), which is larger than the MR DFOV. Fifth, the PET TOF-NAC image is used to determine the patient's body surface contour or outline (e.g., using the Chan-Vese active contour estimation algorithm). Sixth, the body surface contour/outline is used to produce a binary body mask 18. Seventh, the MR/pseudo-CT mask and the binary body mask are co-registered with each other as shown in FIG. 6, and any regions 20 that are truncated (i.e., appearing in the PET-derived binary body mask, but not appearing in the MR/pseudo-CT mask) are identified. Eighth, the MR/pseudo-CT mask is corrected by “filling in” the truncated regions 20 (i.e., “truncation completion”). Finally, the corrected MR/pseudo-CT mask 22 as shown in FIG. 7 (in which the filled-in formerly truncated arm region 20 is shown in cross-hatching) is used for MR-based attenuation completion of the PET images. However, because of the distortion that occurs in MR images toward the edges of the MR FOV, the foregoing process for MR-based AC may unintentionally include distorted data.
It would be desirable, therefore, to provide an improved system and method for truncation completion and MR-based attenuation correction for PET and PET/MR which mitigates the abovementioned shortcomings, and which provides advantages that are not found in the prior art approaches.